A developer significantly reduced the token costs associated with using Claude Code for code reviews by implementing a more targeted approach. Instead of feeding the entire codebase to the AI, the developer limited the context to only the files within two hops of the code changes. This method, utilizing Tree-sitter to build a call graph, reduced token bills by 8x to 49x depending on the repository size and complexity, while also improving review quality. AI
IMPACT Demonstrates a practical method to reduce LLM inference costs for code analysis tools by optimizing context window usage.
RANK_REASON Developer shares a practical technique for optimizing an existing AI tool's cost and performance.
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